The rumen microbial metagenome associated with high methane production in cattle

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Abstract

Background: Methane represents 16 % of total anthropogenic greenhouse gas emissions. It has been estimated
that ruminant livestock produce ca. 29 % of this methane. As individual animals produce consistently different quantities
of methane, understanding the basis for these differences may lead to new opportunities for mitigating ruminal methane
emissions. Metagenomics is a powerful new tool for understanding the composition and function of complex microbial
communities. Here we have applied metagenomics to the rumen microbial community to identify differences in the
microbiota and metagenome that lead to high- and low-methane-emitting cattle phenotypes.
Methods: Four pairs of beef cattle were selected for extreme high and low methane emissions from 72 animals,
matched for breed (Aberdeen-Angus or Limousin cross) and diet (high or medium concentrate). Community analysis was
carried out by qPCR of 16S and 18S rRNA genes and by alignment of Illumina HiSeq reads to the GREENGENES database.
Total genomic reads were aligned to the KEGG genes databasefor functional analysis.
Results: Deep sequencing produced on average 11.3 Gb per sample. 16S rRNA gene abundances indicated that archaea,
predominantly Methanobrevibacter, were 2.5× more numerous (P = 0.026) in high emitters, whereas among bacteria
Proteobacteria, predominantly Succinivibrionaceae, were 4-fold less abundant (2.7 vs. 11.2 %; P = 0.002). KEGG analysis
revealed that archaeal genes leading directly or indirectly to methane production were 2.7-fold more abundant in high
emitters. Genes less abundant in high emitters included acetate kinase, electron transport complex proteins RnfC and
RnfD and glucose-6-phosphate isomerase. Sequence data were assembled de novo and over 1.5 million proteins were
annotated on the subsequent metagenome scaffolds. Less than half of the predicted genes matched matched a domain
within Pfam. Amongst 2774 identified proteins of the 20 KEGG orthologues that correlated with methane emissions, only
16 showed 100 % identity with a publicly available protein sequence.
Conclusions: The abundance of archaeal genes in ruminal digesta correlated strongly with differing methane emissions
from individual animals, a finding useful for genetic screening purposes. Lower emissions were accompanied by higher
Succinovibrionaceae abundance and changes in acetate and hydrogen production leading to less methanogenesis, as
similarly postulated for Australian macropods. Large numbers of predicted protein sequences differed between high- and
low-methane-emitting cattle. Ninety-nine percent were unknown, indicating a fertile area for future exploitation.